text: """ An example of the 'science' theme. """
  
  import numpy as np 
  import matplotlib.pyplot as plt 
  
  def model(x, p):
      return x ** (2 * p + 1) / (1 + x ** (2 * p))
  
  x = np.linspace(0.75, 1.25, 201)
  
  with plt.style.context(['science']):
      fig, ax = plt.subplots()
      for p in [10, 15, 20, 30, 50, 100]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig1.pdf')
      fig.savefig('figures/fig1.jpg', dpi=300)
  
  with plt.style.context(['science', 'ieee']):
      fig, ax = plt.subplots()
      for p in [10, 20, 50]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig2.pdf')
      fig.savefig('figures/fig2.jpg', dpi=300)
  
  with plt.style.context(['science', 'scatter']):
      fig, ax = plt.subplots(figsize=(4,4))
      ax.plot([-2, 2], [-2, 2], 'k--')
      ax.fill_between([-2, 2], [-2.2, 1.8], [-1.8, 2.2], color='dodgerblue', alpha=0.2, lw=0)
      for i in range(7):
          x1 = np.random.normal(0, 0.5, 10)
          y1 = x1 + np.random.normal(0, 0.2, 10)
          ax.plot(x1, y1, label=r"$^\#${}".format(i+1))
      ax.legend(title='Sample', loc=2)
      ax.set_xlabel(r"$\log_{10}\left(\frac{L_\mathrm{IR}}{\mathrm{L}_\odot}\right)$")
      ax.set_ylabel(r"$\log_{10}\left(\frac{L_\mathrm{6.2}}{\mathrm{L}_\odot}\right)$")
      ax.set_xlim([-2, 2])
      ax.set_ylim([-2, 2])
      fig.savefig('figures/fig3.pdf')
      fig.savefig('figures/fig3.jpg', dpi=300)
  
  with plt.style.context(['science', 'high-vis']):
      fig, ax = plt.subplots()
      for p in [10, 15, 20, 30, 50, 100]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig4.pdf')
      fig.savefig('figures/fig4.jpg', dpi=300)
  
  with plt.style.context(['dark_background', 'science', 'high-vis']):
      fig, ax = plt.subplots()
      for p in [10, 15, 20, 30, 50, 100]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig5.pdf')
      fig.savefig('figures/fig5.jpg', dpi=300)
  
  with plt.style.context(['science', 'notebook']):
      fig, ax = plt.subplots()
      for p in [10, 15, 20, 30, 50, 100]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig10.pdf')
      fig.savefig('figures/fig10.jpg', dpi=300)
  
  # Plot different color cycles 
  
  with plt.style.context(['science', 'bright']):
      fig, ax = plt.subplots()
      for p in [5, 10, 15, 20, 30, 50, 100]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig6.pdf')
      fig.savefig('figures/fig6.jpg', dpi=300)
  
  with plt.style.context(['science', 'vibrant']):
      fig, ax = plt.subplots()
      for p in [5, 10, 15, 20, 30, 50, 100]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig7.pdf')
      fig.savefig('figures/fig7.jpg', dpi=300)
  
  with plt.style.context(['science', 'muted']):
      fig, ax = plt.subplots()
      for p in [5, 7, 10, 15, 20, 30, 38, 50, 100, 500]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order', fontsize=7)
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig8.pdf')
      fig.savefig('figures/fig8.jpg', dpi=300)
  
  with plt.style.context(['science', 'retro']):
      fig, ax = plt.subplots()
      for p in [10, 15, 20, 30, 50, 100]:
          ax.plot(x, model(x, p), label=p)
      ax.legend(title='Order')
      ax.set(xlabel='Voltage (mV)')
      ax.set(ylabel='Current ($\mu$A)')
      ax.autoscale(tight=True)
      fig.savefig('figures/fig9.pdf')
      fig.savefig('figures/fig9.jpg', dpi=300)
  